Search Results - (( data distribution means algorithm ) OR ( pareto distribution model algorithm ))*

Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

“…Generalized extreme value (GEV) distribution and generalized Pareto (GP) distribution are two main models in EV theory based on block maxima and threshold exceedances approaches. …”
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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution: article / Nor Azura Ayop by Ayop, Nor Azura

“…The research scope is based on collected of internet traffic on IP-based network real live traffic at 16 Mbps speed line. Open Distribution Fitting application is fitted to the collected data to identifying the best distribution and the results presents Generalized Pareto shows the highest value for best fitted traffic model. …”
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Enhanced Micro Genetic Algorithm-Based Models For Multi-Objective Optimization by Tan, Choo Jun

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Rate limiting algorithm on video traffic with Pareto traffic model in broadband network / Rafidah Samsuri by Samsuri, Rafidah

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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop by Ayop, Nor Azura

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4E analysis of a two-stage refrigeration system through surrogate models based on response surface methods and hybrid grey wolf optimizer by Ahmed, R., Mahadzir, S., Mota-Babiloni, A., Al-Amin, M., Usmani, A.Y., Ashraf Rana, Z., Yassin, H., Shaik, S., Hussain, F.

“…Firstly, the interaction between the system components and their cycle behavior is analyzed by building four surrogate models using RSM. The model fit statistics indicate that they are statistically significant and agree with the design data. …”
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NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment by Shen, jiazheng, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan, Wang, Xinming

“…To improve the performance of intelligent products and reasonably distribute the load of the loading robot, a multi-objective, and multi-objective (Traveling-salesman problem, TSP) mathematical model was established. …”
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Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation by Mahesh, K., Nallagownden, P., Elamvazuthi, I.

“…This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. …”
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Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation by Mahesh, K., Nallagownden, P., Elamvazuthi, I.

“…This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. …”
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Hybrid flow shop scheduling problem with energy utilization using non-dominated sorting genetic algorithm-III (NSGA-III) optimization by Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…The model was compared with the most sought algorithm and latest multi-objective algorithms, Strength Pareto Evolutionary Algorithm 2 (SPEA -II), Multi-Objective Algorithm Particle Swarm Optimization (MOPSO), Pareto Envelope-based Selection Algorithm II (PESA-II) and Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D). …”
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Optimal placement and sizing of renewable distributed generations and capacitor banks into radial distribution systems by Mahesh, K., Nallagownden, P., Elamvazuthi, I.

“…The intermittency of wind speed and solar irradiance are handled with multi-state modeling using suitable probability distribution functions. …”
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Novel distributed algorithm for coalition formation for enhanced spectrum sensing in cognitive radio networks by Tahir, Mohammad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul

“…In the proposed model, we extend the stable matching problem to propose a novel algorithm to form coalitions of varying sizes for improving the utility of cognitive radios (false alarm and throughput). …”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

“…Further more, an improved non-dominated sorting genetic algorithm with an elite strategy II (IMNSGA-II) has been developed to solve the two bi-objective models, surpassing existing literature’s algorithms such as Pareto Envelope-based Selection Algorithm II (PESA-II) and NSGA-II. …”
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Novel distributed algorithm for coalition formation in cognitive radio networks for throughput enhancement using matching theory by Tahir, Mohammad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul

“…In the proposed model, the stable matching problem is extended to propose a novel algorithm to form coalitions of varying sizes for improving the utility of CR (false alarm and throughput). …”
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Bi-objective mixed integer nonlinear programming model for low carbon location-inventory-routing problem with time windows and customer satisfaction by Liu, Lihua, He, Aneng, Tian, Tian, Lee, Lai Soon, Seow, Hsin-Vonn

“…An improved non-dominated sorting genetic algorithm II (IMNSGA-II) with an elite strategy is developed to solve the model. …”
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Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm by Khoo, Thau Soon

“…Our algorithm uses non-fitness evolutionary distributed parallelized adaptive large neighbourhood search (NEDPALNS). …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”

Multi-objective optimization of all-wheel drive electric formula vehicle for performance and energy efficiency using evolutionary algorithms by Tey, Jing Yuen, Ramli, Rahizar

“…Results show that the non-dominated sorting genetic algorithm II outperforms the constrained multi-objective evolutionary algorithm based on decomposition by using differential evolution in obtaining a wider distributed Pareto solution and converges at a relatively shorter time frame. …”
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